MOSEK is a software package for solving large scale sparse optimization problems. To be precise MOSEK is capable of solving linear, convex quadratic and conic quadratic optimization problems possibly having some integer constrained variables. In addition MOSEK can solve continuous semidefinite optimization problems.
In this presentation we will review what is new and improved in the recently released version 8. We will also present computational results that documents upgrading to MOSEK version 8 provides a genuine enhancement of the numerical stability and performance.
The results also documents that MOSEK is one of the best if not the best semidefinite optimizer.
Erling D. Andersen is one of the founders of and current CEO of MOSEK APS a leading maker of optimization software for linear and conic optimization problems. Erling has a Ph.D. from Odense University in Denmark and has worked with optimization algorithms and their implementation over the last 25 years. He has published several papers in journals such as Mathematical Programming and SIAM Journal of Optimization.